Systems and methods for telematics montoring and communications

ABSTRACT

Certain example embodiments of the disclosed technology may include systems and methods for telematics monitoring. An example method is provided that includes receiving, at a mobile computing device, and from a Vehicle Identification Unit (VIU), identification (ID) data representing a first vehicle. The method further includes receiving, by the mobile computing device, sensor data from one or more sensors associated with the mobile computing device. Certain embodiments may further include receiving, at an Operational Measurement Unit (OMU), an operation indication associated with the first vehicle. The OMU may include an operational measurement component configured to advance an operational count in response to receiving the operation indication. Certain example embodiments may include transmitting telematics data by the mobile computing device. In certain embodiments, the telematics data may include least a portion of one or more of the ID data, the sensor data, and/or the operational count data.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.13/796,717, filed on 12 Mar. 2013, and published as US2013/0190967 on 25Jul. 2013, and entitled “Systems and Methods for Telematics Monitoringand Communications.” U.S. patent application Ser. No. 13/796,717 is acontinuation-in-part of U.S. patent application Ser. No. 13/350,388,filed on 13 Jan. 2012, and entitled “Telematics Smart Pinging Systemsand Methods.” U.S. patent application Ser. No. 13/796,717 is also acontinuation-in-part of U.S. patent application Ser. No. 13/012,400,filed on 24 Jan. 2011, and entitled “Telematics Smart Pinging Systemsand Methods,” the contents of which are hereby incorporated by referencein their entirety. U.S. patent application Ser. No. 13/796,717 claimspriority to U.S. Provisional Patent application Ser. No. 61/738,436,filed on 18 Dec., 2012, entitled: “Systems and Methods for TelematicsMonitoring and Communications,” the contents of which are herebyincorporated by reference in their entirety.

This application is related to PCT applications PCT/US2012/022413, filedon 24 Jan. 2012, and PCT/US2013/021423, filed on 14 Jan. 2013, eachentitled “Telematics Smart Pinging Systems and Methods,” the contents ofwhich are hereby incorporated by reference in their entirety.

TECHNICAL FIELD

Various embodiments of the disclosed technology relate to telematicsmonitoring and communication systems and methods, and more particularly,to cost-effective telematics systems and methods for monitoringvehicular and operator data.

BACKGROUND

One of the challenges faced by many businesses involves determiningaccurate risk factors associated with individuals. For example,insurance providers may set rates for applicants based on their known orassumed risk factors. A conventional method for determining riskutilizes general personal information such as age, sex, marital status,driving record, etc. The general personal information, along withactuarial, statistical, or empirical data associated with the generalpopulation is then utilized to help categorize individuals and setappropriate insurance rates. However, the individual may exhibit certainbehaviors and habits, or may intermittently engage in high-riskactivities that are not reflected in the general personal information,and the actual risk factors may differ widely from person-to-personwithin a given actuarial category.

In certain situations, it may be desirable to know the actual identityof a person involved in a specific incident. However, the generalpersonal information is often insufficient for determining the habits,behaviors, or the actual identity of an individual. Conventional methodsused by insurance providers to determine costs of motor vehicleinsurance involve gathering relevant personal data from the applicantand referencing the applicant's public motor vehicle driving records andhistorical accident data. Such data generally results in aclassification of the applicant to a broad actuarial class for whichinsurance rates are assigned based upon empirical experiences of aninsurance provider. Various factors can be relevant to classification ina particular actuarial class, such as age, sex, marital status, homelocation, and driving record. Based on the personal data received fromand about the applicant, the insurance provider can assign the applicantto an actuarial class and then assign an insurance premium based on thatactuarial class.

Because a selected insurance premium is dependent on the applicant'spersonal data, a change to that personal data can result in a differentpremium being charged if the change results in a different actuarialclass for the applicant. For instance, if a first actuarial classincludes drivers between the ages of 36 and 40, and a second actuarialclass includes drivers between the ages of 41 and 45, then a change inthe applicant's age from 38 to 39 may not result in a differentactuarial class, but a gradual change from 38 to 45 may result in achanged actuarial class and thus a changed insurance premium.

A principal issue associated with these conventional insurancedetermination systems is that the personal data collected from theapplicant is generally not verifiable. For instance, the insuranceprovider may have no means to verify the applicant's mileage per year orthe applicant's driving styles, either of which can be relevant to theselected insurance premium. Accordingly, the insurance provider'scategorization of the applicant into a certain actuarial class may bebased on false or incomplete information about the applicant, which canin turn result in an insurance premium that does not accurately reflectthe risk of insuring the applicant.

BRIEF SUMMARY

Some or all of the above needs may be addressed by certain embodimentsof the disclosed technology. Certain embodiments of the disclosedtechnology may include systems and methods for telematics monitoring.Certain embodiments of the disclosed technology may include systems andmethods for scenario analysis and assertion.

Embodiments of the disclosed technology include systems and methods fortelematics monitoring and communications. Briefly described, variousembodiments of the disclosed technology may include systems and methodsfor monitoring driving behavior and/or motor vehicle telematic datathrough various combinations of devices that can include (1) one or moreperipheral devices; (2) a mobile computing device configured for sensingcertain phenomena and for receiving information from the one or moreperipheral devices; and (3) a server in communication with the mobilecomputing device, and configured for receiving data from the mobilecomputing device.

According to certain example implementations of the disclosedtechnology, the data transmitted from the mobile computing device to theserver may include telematic data derived from various combinations ofthe information received from the peripheral devices and/or from sensorsassociated with mobile computing device. Embodiments of the disclosedtechnology provide systems and methods for determining if a vehicle hasbeen operated without being monitored by the mobile computing device.According to certain example embodiments of the disclosed technology, aparticular vehicle may be positively identified by identification (ID)information received from a Vehicle Identification Unit. In anotherexample embodiment, a particular vehicle may be identified viainformation provided by other in-car hardware. According to certainexample embodiments of the disclosed technology, a particular vehiclemay be identified by vibration, sound, or other phenomena that may besensed by the mobile computing device.

A computer-implemented method is provided for receiving, at anOperational Measurement Unit (OMU), an operation indication associatedwith a first vehicle. The OMU includes an operational measurementcomponent configured to advance an operational count in response toreceiving the operation indication. The method further includesreceiving, at a Vehicular Identification Unit (VIU), vehicularidentification data related to the first vehicle, wherein the vehicularidentification data includes identification (ID) data representing thefirst vehicle. The method further includes transmitting the operationalcount and the ID data wirelessly to a mobile computing device;receiving, at the mobile computing device, the transmitted operationalcount and the ID data; receiving, with the mobile computing device,sensor data from one or more sensors associated with the mobilecomputing device; and transmitting, by the mobile computing device to aremote server, telematics data, wherein the telematics data comprises atleast a portion of one or more of the operational count, the ID data,and the sensor data.

Another computer-implemented method is provided, according to an exampleimplementation, for receiving, at a mobile computing device, and from aVehicle Identification Unit (VIU), identification (ID) data representinga first vehicle. The method may include receiving, by the mobilecomputing device, sensor data from one or more sensors associated withthe mobile computing device; and transmitting, by the mobile computingdevice, telematics data, wherein the telematics data includes at least aportion of one or more of the ID data and the sensor data.

In certain embodiments, a method may include receiving, at anOperational Measurement Unit (OMU), an operation indication associatedwith the first vehicle. The OMU may include an operational measurementcomponent configured to advance an operational count in response toreceiving the operation indication. The method may include transmittingdata representing the operational count wirelessly to the mobilecomputing device; receiving, at the mobile computing device, thetransmitted operational count data; transmitting, by the mobilecomputing device, the telematics data, wherein the telematics datafurther comprises the operational count data.

A system is provided, according to an example implementation. The systemincludes an a vehicle identification unit (VIU), wherein the VIU isconfigured to provide identification (ID) data corresponding to aspecific vehicle, wherein the VIU includes a transmitter for wirelesslytransmitting the ID data. The system includes a mobile computing devicethat includes one or more sensors, at least one memory for storing dataand computer-executable instructions, and at least one processorconfigured to access the at least one memory and further configured toexecute the computer-executable instructions to receive the ID data fromthe VIU, receive sensor data from the one or more sensors, and transmittelematics data, wherein the telematics data may include at least aportion of one or more of the ID data and the sensor data.

A computer-readable media is also provided. The computer-readable mediamay be non-transient, and may store instructions that, when executed,cause one or more processors to perform a method for receiving, at amobile computing device, and from a Vehicle Identification Unit (VIU),identification (ID) data representing a first vehicle. The method mayinclude receiving, by the mobile computing device, sensor data from oneor more sensors associated with the mobile computing device; andtransmitting, by the mobile computing device, telematics data, whereinthe telematics data includes at least a portion of one or more of the IDdata and the sensor data.

Other embodiments, features, and aspects of the disclosed technology aredescribed in detail herein and are considered a part of the claimeddisclosed technologies. Other embodiments, features, and aspects can beunderstood with reference to the following detailed description,accompanying drawings, and claims.

BRIEF DESCRIPTION OF THE FIGURES

Reference will now be made to the accompanying figures and flowdiagrams, which are not necessarily drawn to scale, and wherein:

FIG. 1 illustrates an example block diagram of a telematics monitoringsystem, according to an example implementation of the disclosedtechnology.

FIG. 2 illustrates an example block diagram of wireless communicationsbetween a vehicle identification unit device and a mobile computingdevice according to an example embodiment of the disclosed technology.

FIG. 3 illustrates an example block diagram of a computing devicearchitecture, according to an example embodiment of the disclosedtechnology.

FIG. 4 depicts an illustrative webpage user interface with monitoredtelematics data, according to an example implementation of the disclosedtechnology.

FIG. 5 depicts a method flow diagram, according to an example embodimentof the disclosed technology.

FIG. 6 is a block diagram of an illustrative system usage scenario 600according to an example embodiment of the disclosed technology.

FIG. 7 is an illustrative example telematics system 700, according to anexample embodiment of the disclosed technology.

FIG. 8 is a block diagram of an illustrative entity scenario andassertion process 800, according to an example embodiment of thedisclosed technology.

FIG. 9 is a flow diagram of another method according to an exampleembodiment of the disclosed technology.

DETAILED DESCRIPTION OF THE DISCLOSED TECHNOLOGY

Embodiments of the disclosed technology will be described more fullyhereinafter with reference to the accompanying drawings, in whichembodiments of the disclosed technology are shown. This disclosedtechnology may, however, be embodied in many different forms and shouldnot be construed as limited to the embodiments set forth herein; rather,these embodiments are provided so that this disclosure will be thoroughand complete, and will fully convey the scope of the disclosedtechnology to those skilled in the art.

In the following description, numerous specific details are set forth.However, it is to be understood that embodiments of the disclosedtechnology may be practiced without these specific details. In otherinstances, well-known methods, structures and techniques have not beenshown in detail in order not to obscure an understanding of thisdescription. References to “one embodiment,” “an embodiment,” “exampleembodiment,” “various embodiments,” etc., indicate that theembodiment(s) of the disclosed technology so described may include aparticular feature, structure, or characteristic, but not everyembodiment necessarily includes the particular feature, structure, orcharacteristic. Further, repeated use of the phrase “in one embodiment”does not necessarily refer to the same embodiment, although it may. Asused herein, unless otherwise specified the use of the ordinaladjectives “first,” “second,” “third,” etc., to describe a commonobject, merely indicate that different instances of like objects arebeing referred to, and are not intended to imply that the objects sodescribed must be in a given sequence, either temporally, spatially, inranking, or in any other manner.

As used herein, unless otherwise specified, the terms “mobile device” or“mobile computing device” may include a cellular phone, a smart phone, atablet computer, a handheld mobile computing device, or a wearablemobile device that may be owned, carried, and/or utilized, for example,by an individual during the normal activities, which may includeoperating a vehicle. In certain example implementations of the disclosedtechnology, the mobile computing device may include devices utilized insystems such as OnStar, Chevrolet MyLink, Advanced Automatic CollisionNotification, MyFord Touch, Ford Sync, BMW Assist, Dashtop mobile, GPStracking, Lexus Link, Lojack Transmitters, and the like.

As used herein, unless otherwise specified, the terms “VehicleIdentification Unit,” “vehicle identification unit,” or “VIU,” may referto a device utilized in conjunction with a vehicle. In certain exampleembodiments, the VIU may be utilized primarily for positivelyidentifying a particular vehicle. According to certain exampleimplementations of the disclosed technology, the VIU may be utilized inconjunction with vehicle identification (ID) data (for example,monitoring, receiving, storing, transmitting, etc.). As used herein,unless otherwise specified, the term “vehicle ID data” may include anynumber of types of data, including, but not limited to one or more of:vehicle identification information, IP address information and/or MACaddress information from in-vehicle components, Bluetooth communicationspairing data, data from an on-board diagnostics (OBD) port, voltagelevels, vacuum levels, vibration, odometer readings, engine revolutionsper minute, fuels levels, etc.

In other example embodiments, the VIU may provide additional functions.In certain example embodiments, the VIU may be a component of systemsthat may be configured perform functions associated with the VIU andother functions, as will be discussed below.

As used herein, unless otherwise specified, the terms “OperationalMeasurement Unit,” “operational measurement unit,” or “OMU,” may referto a device for measuring operational count, representation of duration,or time. In certain example embodiments, the OMU device may beconfigured to advance a count when a signal such as an operationindication is received. Devices of this type may include, but are notlimited to a Hobbs meter, a vehicle power activated timer, counter, orclock, a vibration activated timer, counter, or clock, etc. In certainexample embodiments, the OMU may be utilized primarily for measuringoperational time, a representation of operational duration, and/or anadvancing (and stored) count associated with an operation of a vehicle.In certain example embodiments, the OMU may be a component or part of asystem that may be configured perform functions associated with the OMUin addition to other functions, such as VIU functions, or VDU functions(as will be explained below).

As used herein, unless otherwise specified, the terms “Vehicle DataUnit,” “vehicle data unit,” or “VDU,” may refer to a device utilized inconjunction with a vehicle to receive and/or transmit vehicular data. Asused herein, unless otherwise specified, the term “vehicular data” mayinclude any number of types of data, including, but not limited to datafrom an on-board diagnostics (OBD) port, voltage levels, vacuum levels,vibration, odometer readings, engine revolutions per minute, fuelslevels, temperature levels, pressure levels, etc. In certain exampleimplementations, the term “vehicular data” may further include one ormore of: IP address information and/or MAC address information fromin-vehicle components, Bluetooth communications pairing data, etc. Incertain example embodiments, such IP/Bluetooth/pairing data may also beassociated with the VIU, as indicated above. The term “vehicular data”may also include data received from any commercial services or devicessuch as those associated with OnStar, Chevrolet MyLink, AdvancedAutomatic Collision Notification, MyFord Touch, Ford Sync, BMW Assist,Dashtop mobile, GPS tracking, Lexus Link, Lojack Transmitters, and thelike.

According to certain example implementations, the VIU, VDU, and OMU mayoperate separately, and/or in combination without limitation. In certainexample embodiments, one or more of the VIU, VDU, and OMU may beincluded in a system. For example, in one embodiment, a combination VIU,VDU, and OMU device may be placed in a vehicle and attached to a port inthe vehicle. In another example implementation, one or more separatedevices may be utilized for the various functions, and the devices mayoperate independent of each other. In example implementation, an OMU maybe utilized without requiring the VIU or VDU. In another exampleimplementation, the VIU may be utilized with the OMU without requiringthe use of the VDU. In certain embodiments, the VDU may utilizevehicular data, and may additionally function as a complete OMU. Inanother embodiment, the VDU may function as a unit that receives and/ortransmits vehicular data, provides OMU functions, and also provides VIUfunctions. It should be readily apparent that any combination orpermutation of one or more of these three units may be utilizedaccording to example embodiments of the disclosed technology.

According to one example embodiment, the devices such as thoseassociated with OnStar, Chevrolet MyLink, Advanced Automatic CollisionNotification, MyFord Touch, Ford Sync, BMW Assist, Dashtop mobile, GPStracking, Lexus Link, Lojack Transmitters, and the like, may beconsidered as a VIU, depending on the provided functions and use of theprovided data. In another example implementation, such devices may beconsidered as a VDU depending on the provided functions the use of theprovided data. In other example embodiments, such devices may beconsidered as an OMU depending on the provided functions and provideddata.

Certain example embodiments of the disclosed technology may enable amobile computing device to be utilized as a monitoring and/orcommunications device for obtaining and/or communicating informationrelated to certain activities associated with a user of the mobilecomputing device, including information related to the operation of amotor vehicle. Example embodiments of the disclosed technology may alsoprovide for the use of the mobile computing device in conjunction withone or more peripheral devices that may communicate vehicular data,vehicular identification, and/or operational duration data to the mobilecommunication device. In certain example embodiments, the one or moreperipheral devices may communicate certain data wirelessly to the mobilecomputing device.

According to an example implementation, data obtained by the systems andmethods described herein may be provided by, or on behalf of, insurancecarriers, employers, transportation manufacturers including, but notlimited to, private passenger and fleet automobile motorcycle, capitalfarm and construction equipment, motor home, and trucking manufacturers,government entities and individual consumers for the purposes ofdetermining driving performance of a specific vehicle or driver.

Although embodiments of the disclosed are anticipated to be useful forthe insurance industry, certain systems and methods disclosed herein maybe utilized in a wide variety of applications. For example, in certainembodiments, employers may use the disclosed technology for maintenance,training, and HR purposes. In certain embodiments, vehicles may betracked and based on pre-existing knowledge of a vehicle. In certainembodiments, information received from the vehicle may be utilized tobuild a knowledge base, for example, a programmatic methodology utilizethe disclosed technology to design maintenance schedules andreplacements. In accordance with an example embodiment, driversassociated with an assigned vehicle may be effectively monitored foradherence to performance based guidelines such as obeying traffic lawsand speed limits, as well as defined company standards. Other users ofembodiments of the disclosed technology may include, but are not belimited to, government agencies (for insurance, humanresource/employment, traffic safety/research purposes), youthful, newlylicensed, and restricted driver/vehicle monitoring programs, (and otherdefined and undefined purposes), commercial fleet management of vehiclesin service, rental agencies (private passenger automobile and commercialrental (vehicle or equipment) for rental, usage, geo-fencing and assettracking), and consumer protection applications related to a vehicle'shistory and operational background (example: Carfax, Autocheck vehiclehistory services). Embodiments of the disclosed technology may also beimplemented as a process for collecting data to be used for thefollowing insurance and non-insurance related purposes: advertising andmarketing; site selection; transportation services; land use planning;determining road design, surface or composition; traffic planning anddesign; and road conditions.

According to an example embodiment, the mobile computing device may beconfigured with at least one processor, and a memory in communicationwith the at least one processor that stores data and instructions. Theinstructions, for example, may be embodied as a mobile application, thatwhen executed by the at least one processor may cause the mobilecomputing device to monitor/gather/communicate information related tocertain activities associated with a user of the mobile computing deviceand/or the information related to the operation of a motor vehicle. Inan example embodiment of the disclosed technology, activities related torisk of operating a vehicle (such as speed, braking, etc.,) may bemonitored. In another example embodiment of the disclosed technology,activities that may not be necessarily related to risk of operating avehicle (such as ignition operation time, fluid levels, etc.,) may bemonitored.

Certain example embodiments of the disclosed technology may enableidentifying individuals based on information received from their mobilecomputing device. Example embodiments of the disclosed technology mayutilize scenario and/or assertion analysis in the determination ofinformation about the individual in possession of a mobile device. Forexample, individuals generally hold their mobile phones or computingdevices in a certain way while taking and/or walking. Some individuals,for example, utilize hands-free devices, while other individuals holdtheir mobile device predominantly in either the left hand or the righthand. According to an example embodiment, sensors in the mobile device,such as accelerometers and/or gyroscopes, magnetometers, etc., may beutilized to detect the tilt angle of the device, and may be utilized todistinguish one user of the device from another user.

In accordance with an example embodiment of the disclosed technology, awalking “signature” of an individual, may be detected by sensorsassociated with the mobile device. For example, information such asglobal positioning system (GPS) data, accelerometer data, magnetometerdata, and/or gyroscope data may be analyzed and/or compared withpreviously obtained information to determine phone tilt, location,oscillation, movement signatures, etc. According to certain exampleembodiments, such information and analysis may be utilized todistinguish one user of the device from another user. Other exampleembodiments may utilize other various sensors associated with the mobilecomputing device, including the microphone, clock data, Bluetooth data,and/or Wi-Fi system data to extract information about the user. Forexample, the information obtained from the mobile device may be utilizedfor identifying one or more of an individual in possession of, orassociated with the mobile computing device, characteristics of anindividual in possession of or associated with the mobile computingdevice, and/or one or more vehicles in proximity to the mobile device.

According to example embodiments of the disclosed technology,information related to the mobile computing device tilt, location,oscillation, vibration, movement signatures, etc., may form a “userfingerprint” that may be utilized for establishing primary or secondaryevidence. For example, an insurance company may investigate a car wreckwhere the insured claims that he/she was not driving the car. Exampleembodiments of the disclosed technology may be utilized to draw certainconclusions about who was driving, how fast they were going at the timeof the accident, if there were any risky or abnormal behaviors prior tothe accident, etc.

A mobile computing device solution is disclosed herein in variousembodiments that may utilize an insurance policyholder's own mobilecomputing device (such as a smart phone or the like) to leveragecellular data and on-device functionality of the mobile communicationdevice in such a way that may provide carriers a cost-effective optionfor deployment driving behavior tracking technology. Because of the needto positively identify when driving is taking place, the addition of avehicle identification unit (VIU) is disclosed herein. In one exampleimplementation, the VIU may be attached to the on-board-diagnostic (OBD)port of the vehicle. In another example implementation, the VIU devicemay be supplied by the original equipment manufacturer (OEM). In anotherexample implementation, the in-vehicle VIU device may be an aftermarketdevice that can positively identify the vehicle (for example, via GMOnStar, Ford Sync, a hands-free speakerphone interface, or othertechnology as previously discussed). According to other exampleimplementations, the VIU device may be configured to plug into a port onthe vehicle that may supply power to the device and/or providecommunications with another component associated with the vehicle. Theport may be, for example, standard or custom, and may include (but isnot limited to) a USB port, cigarette lighter outlet, etc. According toan example implementation, a wireless communication link from the VIU tothe policyholder's smartphone may be implemented, for example, viaBluetooth or any other suitable communications method.

Certain example implementations of the disclosed technology may monitor,analyze, and utilize telematic information for various purposesincluding, but not limited to, determining premiums for auto insurancepurposes. For example, by utilizing the various embodiments disclosedherein, certain monitored data may indicate dangerous and/or safedriving behaviors, habits etc., and such data may be monitored directlywhile a subject drives a vehicle. In certain example embodiments of thedisclosed technology, the monitored information may be stored, analyzed,and utilized for various purposes, including but not limited toassessing the risk of a particular driver having an accident,calculating insurance premiums accordingly, providing feedback for thedriver or entities associated with the driver (for example, parents ofteen driver), marketing activities, traffic planning, safety studies,etc. According to one example use case, a driver who drives longdistance at high speed may be charged a higher insurance rate than adriver who drives short distances at slower speeds.

Various systems and techniques may be utilized for identity analysis andassertion verification, according to example embodiments of thedisclosed technology. Example embodiments of the disclosed technologymay provide for the utilization of a mobile computing device as amonitoring and/or communications device for obtaining and/orcommunicating information related to certain activities associated witha user of the mobile computing device, including information related tothe operation of a motor vehicle. These and other aspects of thedisclosed technology will now be described with reference to theaccompanying figures.

FIG. 1 illustrates an example block diagram of a telematics monitoringsystem, according to an example implementation of the disclosedtechnology. In an example implementation, one or more peripheral devices104 may be installed or placed in or on a vehicle 102. In one exampleembodiment, the one or more peripheral devices 104 may be connected to aport 110 associated with the vehicle 102. In one embodiment, the port110 may be an on-board-diagnostic (OBD) port. As discussed above, andaccording to another example embodiment, the port 110 may be a USB port.According to other example embodiments, the port 110 may be cigarettelighter port.

In accordance with certain example embodiments of the disclosedtechnology, the one or more peripheral devices 104 may include one ormore combinations of a Vehicle Identification Unit (VIU) 103, a VehicleData Unit (VDU) 105, and an Operational Measurement Unit (OMU) 107. Someof the various embodiments, combinations, operation, etc. associatedwith the VIU 103, VDU 105, and OMU 107 were discussed above with regardto example definitions of these acronyms.

According to an example embodiment, a driver 108 of the vehicle 102 maypossess, own, or otherwise carry with them, a mobile computing device106. In this example figure, the mobile computing device may be referredto as a smartphone 106. In an example implementation, a special-purposemobile application may be downloaded and installed on the smartphone106, and may run in the background. In an example implementation, theone or more peripheral devices 104 may include one or more wirelesstransceivers or transmitters that may provide wireless communications112 to the smartphone 106. For example, any data that is presented toand/or generated, alone or in combination, by the VIU 103, VDU 105,and/or OMU 107 may be transmitted to the smartphone 106 via the wirelesscommunications 112 channel. In another example implementation, the oneor more peripheral devices 104 may be configured with a communicationshard-wired port for programming and/or wired communications.

In one embodiment, the port 110 may be an on-board diagnostic (OBD) portassociated with the vehicle. In this embodiment, the one or moreperipheral devices 104 may be connected to the OBD port, for example, toreceive power and/or OBD data. The mobile application running on thesmartphone 106, for example, may be configured to allow the smartphone106 to detect when it is in the presence of the one or more peripheraldevices 104, and may cause the smartphone 106 to pair with one or moreof the peripheral devices 104 and setup a wireless communications 112channel whenever the smartphone 106 is within the wireless range of theone or more peripheral devices 104. In one example embodiment, thewireless range may be less than 10 feet. In other example embodiments,the wireless range may be less than 5 feet. According to an exampleimplementation, the smartphone 106 may wirelessly receive data from theone or more peripheral devices 104.

In accordance with example embodiments of the disclosed technology, theterm “telematic data,” (for example, the telematic data 116) may include(but is not limited to) various combinations of one or more of mobiledevice sensor data 116 (which, for example, may be provided by sensorsassociated with the smartphone 106 or other peripheral devices),vehicular data 111 (which, for example, may be provided by the VDU 105),operational measurement data 115 (which, for example, may be provided bythe OMU 107, and/or vehicle ID data 113 (which, for example, may beprovided by the VIU 103. Note that the VIU 103, VDU 105, and OMU 107,along with the respective data 113, 111, 115 are depicted in dashed-lineboxes, indicating that various embodiments disclosed herein may includecombinations of one or more of these devices. Furthermore, theconnection to the port 110 is indicated in dashed lines to indicate thatvarious embodiments disclosed herein may utilize information and/orpower from the port, while other embodiments disclosed herein may notneed to utilize the information and/or power from the port. Inaccordance with an example implementation of the disclosed technology,the mobile computing device, (for example, the smartphone 106) mayreceive sensor data from one or more of the associated VDU 105, OMU 107,or VIU 103 units. For example, the OMU 107 may provide to the mobilecomputing device, time information, which may be considered as sensordata. In other example embodiments, the mobile computing device (forexample, the smartphone 106) may receive sensor data from sensors thatare physically included on or within the mobile computing device.

In accordance with an example implementation of the disclosedtechnology, data received from a port 110 (for example, an OBD port, orother device associated with the vehicle 102) may provide certain paringdata, peripheral device MAC address data, vehicle identification data,operational duration count data, etc., than may also be consideredcollectively as telematic data 116. As discussed above, one or moresensors associated with the smartphone 106 may be utilized tosense/gather certain mobile device sensor data 114 associated withoperation of the vehicle 102 and/or signature information associatedwith the driver 108 and/or insured entity. For example, Table 1 belowlists some of the example mobile device sensor data 114 that may bemonitored via the smartphone 106. Other mobile device sensor data 114not listed in Table 1 may be available for monitoring, and may beutilized without departing from the scope of the disclosed technology.

TABLE 1 Example mobile computing device (smartphone) sensor data 114 RAWMobile Application Data Element Sensor Name or CALCULATED Description[email] N/A Email Address of Policy Holder [id] N/A Unique ID assignedto the participant [SystemID] TELEPHONY_API CDMA System ID [BaseStationTELEPHONY_API CDMA Base Station Longitude Longitude] [BaseStation]TELEPHONY_API CDMA Base Station ID [Accuracy] GPS Returns the accuracyof the fix in meters [PhoneType] TELEPHONY_API PhoneType [AccelerationZ]ACCELEROMETER Acceleration on the z-axis [AccelerationY] ACCELEROMETERAcceleration on the y-axis [AccelerationX] ACCELEROMETER Acceleration onthe x-axis [Inclination] CALCULATED inclination [BaseStationLatitude]TELEPHONY_API CDMA Base Station Latitude [Roll] ORIENTATION rotationaround y-axis (−90 to 90), with positive values when the x-axis movestoward the z-axis [Speed] GPS Returns the speed of the device overground in meters/second. [Altitude] GPS Returns the altitude of this fix[Time] GPS Returns the UTC time of this fix, in milliseconds since Jan.1, 1970. [NetworkID] TELEPHONY_API CDMA Network ID [Hobbs Time] OBDHobbs Meter Mirrored time count saved on phone [Cid] TELEPHONY_API GSMCid [Battery] BATTERY Battery Level % [Azimuth] ORIENTATION Anglebetween the magnetic north direction and the y- axis, around the z-axis(0 to 359). 0 = North, 90 = East, 180 = South, 270 = West [Lac]TELEPHONY_API GSM Lac [Latitude] GPS Returns the latitude of this fix[Longitude] GPS Returns the longitude of this fix [Bearing] GPS Returnsthe direction of travel in degrees East of true North. [Provider] GPSReturns the name of the provider that generated this fix, or null if itis not associated with a provider [Pitch] ORIENTATION Rotation aroundx-axis (−180 to 180), with positive values when the z-axis moves towardthe y-axis [SessionID] CALCULATED GUID Session identifier for EACHapplication startup [LinearAccelerationX] LINEAR_ACCELEROMETER LinearAcceleration on the x-axis [LinearAccelerationY] LINEAR_ACCELEROMETERLinear Acceleration on the y-axis [LinearAccelerationZ]LINEAR_ACCELEROMETER Linear Acceleration on the z-axis [GeoMagneticX]MAGNETIC Geo Magnetic on the x-axis [GeoMagneticY] MAGNETIC Geo Magneticon the y-axis [GeoMagneticZ] MAGNETIC Geo Magnetic on the z-axis[GravityX] GRAVITY Gravity on the x-axis [GravityY] GRAVITY Gravity onthe y-axis [GravityZ] GRAVITY Gravity on the z-axis [RotationPitch]CALCULATED Rotation around the X axis in radians and positive in thecounter-clockwise direction [RotationRoll] CALCULATED Rotation aroundthe Y axis in radians and positive in the counter-clockwise direction[RotationInclinationX] CALCULATED X Inclination Matrix Value[RotationInclinationY] CALCULATED Y Inclination Matrix Value[RotationInclinationZ] CALCULATED Z Rotation Matrix Value [RotationX]CALCULATED X Rotation Matrix Value [RotationY] CALCULATED Y RotationMatrix Value [RotationZ] CALCULATED Z Rotation Matrix Value[RotationAzimuth] CALCULATED Rotation around the Z axis in radians andpositive in the counter-clockwise direction

In accordance with certain example embodiments of the disclosedtechnology, the telematic data 116 (which in some embodiments mayinclude various combinations of the mobile device sensor data 114,vehicle identification data 113, vehicular data 111, and/or operationalmeasurement data 115) may be transmitted wirelessly by an availablecommunication channel 118 from the smartphone 106 to a server 120. Inone example embodiment, the communication channel 118 may include acellular carrier (not shown). Other communications channels may beutilized for communicating data to the remote server 120, as known tothose skilled in the art, and for brevity, will not be discussed here indetail.

In certain example embodiments, various functions and/or activities maybe carried out or otherwise associated with the server 120. For example,and with continued reference to FIG. 1, the server 120 may include adatabase for storing the received telematic data 116. In certain exampleembodiments, the received telematic data 116 may be analyzed andformatted, for example in an easy to understand report or webpage 124that may be retrieved by a policy holder and/or insurance carrier 122(an example of such a webpage 122 is depicted below in FIG. 4).

According to certain example embodiments, analytics 126 may begenerated, for example, based on telematic data 116 and other variousdata sources may be utilized to generate analytics 126. In certainexample embodiments, the telematic data obtained from a plurality ofdrivers and sources may be analyzed to provide analytics and othervalue-added risk data 128 that may be provided to various insurancecarriers 130, for example to allow risk scoring an individual based onstatistical driving data take from a larger population.

FIG. 2 illustrates a simplified example block diagram of wirelesscommunications between one or more peripheral devices 104 and a mobilecomputing device 106, as discussed above in reference to FIG. 1.Similarly, the according to an example embodiment of the disclosedtechnology, the data 204 derived from sensors associated with thesmartphone 106 may be similar to the data shown above in Table 1.According to an example embodiment, the smartphone 106 may wirelesslycommunicate 206 to a remote server by any available communicationschannels, including but not limited to a cellular carrier, or throughthe Internet 208 via a wireless channel. In one example embodiment, thedata received from the port 110 and/or the one or more peripheraldevices 104 may be saved on the smartphone 106 when communicationschannels are not available, and such data may be loaded up to the remoteserver at a later time, for example, when the smartphone 106 is again ina cellular coverage area or is connected to the Internet 208 via Wi-Fi,for example.

FIG. 3 depicts a block diagram of an illustrative computer systemarchitecture 300 according to an example implementation. Certain aspectsof FIG. 3 may be embodied in the mobile computing device (for example,the mobile device 106 as shown in FIGS. 1 and 2). Certain aspects ofFIG. 3 may also be embodied in the remote server (for example, theserver 120 as shown in FIG. 1). Various implementations and methodsherein may be embodied in non-transitory computer readable media forexecution by a processor. It will be understood that the architecture300 is provided for example purposes only and does not limit the scopeof the various implementations of the communication systems and methods.

The computing device 300 of FIG. 3 includes one or more processors wherecomputer instructions are processed. The computing device 300 maycomprise the processor 302, or it may be combined with one or moreadditional components shown in FIG. 3. For example, in one exampleembodiment, the computing device 300 may be the processor 302. In yetother example embodiments, the computing device 300 may be a mobiledevice, mobile computing device, a mobile station (MS), terminal,cellular phone, cellular handset, personal digital assistant (PDA),smartphone, wireless phone, organizer, handheld computer, desktopcomputer, laptop computer, tablet computer, set-top box, television,appliance, game device, medical device, display device, or some otherlike terminology. In other instances, a computing device may be aprocessor, controller, or a central processing unit (CPU). In yet otherinstances, a computing device may be a set of hardware components. Incertain example implementations of the disclosed technology, the mobilecomputing device may include devices utilized in systems such as OnStar,Chevrolet MyLink, Advanced Automatic Collision Notification, MyFordTouch, Ford Sync, BMW Assist, Dashtop mobile, GPS tracking, Lexus Link,Lojack Transmitters, and the like.

The computing device 300 may include a display interface 304 that actsas a communication interface and provides functions for rendering video,graphics, images, and texts on the display. In certain exampleimplementations of the disclosed technology, the display interface 304may be directly connected to a local display, such as a touch-screendisplay associated with a mobile computing device. In another exampleimplementation, the display interface 304 may be configured forproviding data, images, and other information for an external/remotedisplay 350 that is not necessarily physically connected to the mobilecomputing device. For example, a desktop monitor may be utilized formirroring graphics and other information that is presented on a mobilecomputing device. In certain example implementations, the displayinterface 304 may wirelessly communicate, for example, via a Wi-Fichannel or other available network connection interface 312 to theexternal/remote display 350.

The architecture 300 may include a keyboard interface 306 that providesa communication interface to a keyboard; and a pointing device interface308 that provides a communication interface to a pointing device ortouch screen. Example implementations of the architecture 300 mayinclude an antenna interface 310 that provides a communication interfaceto an antenna; a network connection interface 312 that provides acommunication interface to a network. In an example implementation, aone or more peripheral devices 104 (which may be the same one or moreperipheral devices 104 as shown in FIGS. 1 and 2) may communicatewirelessly with the processor 302 via the antenna interface 310. Incertain implementations, a camera interface 314 may be provided that mayact as a communication interface and provide functions for capturingdigital images from a camera. In certain implementations, a soundinterface 316 may be provided as a communication interface forconverting sound into electrical signals using a microphone and forconverting electrical signals into sound using a speaker. In one exampleembodiment, the sound interface 316 may be utilized to receive audibleinformation, for example, from an engine associated with a vehicle. Inother example embodiments, the sound interface may be utilized tomonitor other sound that may be indicative of an accident, wearingautomobile parts, etc.

According to example implementations, a random access memory (RAM) 318may be provided, where computer instructions and data may be stored in avolatile memory device for processing by the processor 302. According toan example implementation, the architecture 300 includes a read-onlymemory (ROM) 320 where invariant low-level system code or data for basicsystem functions such as basic input and output (I/O), startup, orreception of keystrokes from a keyboard are stored in a non-volatilememory device. According to an example implementation, the architecture300 includes a storage medium 322 or other suitable type of memory (e.g.such as RAM, ROM, programmable read-only memory (PROM), erasableprogrammable read-only memory (EPROM), electrically erasableprogrammable read-only memory (EEPROM), magnetic disks, optical disks,floppy disks, hard disks, removable cartridges, flash drives), where thefiles include an operating system 324, application programs 326 and datafiles 328 are stored. Application programs 326, for example, may includea web browser application, a widget or gadget engine, and or othermobile applications, as necessary for pairing with and receivinginformation from the VIU device 340, and for communications with theremote server.

According to an example implementation, the architecture 300 includes apower source 330 that provides an appropriate alternating current (AC)or direct current (DC) to power components. According to an exampleimplementation, the architecture 300 includes one or more sensors 332that can provide telematics data. Example sensors 332 may include, butare not limited to global position system (GPS) sensors, accelerometers,magnetometers, temperature sensors, clocks, and a compass. Theconstituent devices and the processor 302 may communicate with eachother over a bus 334.

In accordance with an example implementation, the processor 302 hasappropriate structure to be a computer processor. In one arrangement,the computer processor 302 may include more than one processing unit.The RAM 318 interfaces with the computer bus 334 to provide quick RAMstorage to the processor 302 during the execution of software programssuch as the operating system application programs, and device drivers.More specifically, the processor 302 loads computer-executable processsteps from the storage medium 322 or other media into a field of the RAM318 in order to execute software programs. Data may be stored in the RAM318, where the data may be accessed by the computer processor 302 duringexecution. In one example configuration, the device 300 includes atleast 128 MB of RAM, and 256 MB of flash memory.

The storage medium 322 itself may include a number of physical driveunits, such as a redundant array of independent disks (RAID), a floppydisk drive, a flash memory, a USB flash drive, an external hard diskdrive, thumb drive, pen drive, key drive, a High-Density DigitalVersatile Disc (HD-DVD) optical disc drive, an internal hard disk drive,a Blu-Ray optical disc drive, or a Holographic Digital Data Storage(HDDS) optical disc drive, an external mini-dual in-line memory module(DIMM) synchronous dynamic random access memory (SDRAM), or an externalmicro-DIMM SDRAM. Such computer readable storage media allow the device300 to access computer-executable process steps, application programsand the like, stored on removable and non-removable memory media, tooff-load data from the device 300 or to upload data onto the device 300.A computer program product, such as one utilizing a communication systemmay be tangibly embodied in storage medium 322, which may comprise amachine-readable storage medium.

FIG. 4 depicts an illustrative report or webpage user interface 400,with monitored telematic data (for example, telematic data 116 as shownin FIG. 1), according to an example implementation of the disclosedtechnology. The information presented in this example report or webpageuser interface 400 may be similar to the data presented in the report orwebpage 124 as shown in FIG. 1. In accordance with an exampleimplementation, an authorized user may login to a website to view theinformation. In one example embodiment, the authorized user may be theinsured driver. In another example implementation, the authorized usermay be a representative of the insurance carrier. According to anexample implementation, different information may be presented,depending on the credentials of the authorized user and/or or end use ofthe information. As shown in FIG. 4, and according to an exampleembodiment, a person viewing the webpage may select a vehicle 402 forwhich the telematic information is available. In an exampleimplementation, a summary view 404 of the collected data may provideinformation, including but not limited to miles driven, percentage ofthe time that the driving was monitored by the smartphone and OBDdevice, number of trips, average speed, and maximum speed.

In accordance with an example implementation, the report or webpage userinterface 400 may also include certain graphical representations thatpresent the monitored telematics data. For example, anacceleration/deceleration chart 406 may be included to provide anindication of the drivers safety habits related to operating the motorvehicle. For example, a large number of extreme acceleration ordeceleration incidents may be indicative of a driver who may present ahigh risk to the insurance carrier.

Additional data may be collected and presented in graphical format. Forexample, a breakdown of miles driven within certain speed ranges 408 maybe presented, for example, to provide another risk dimension indication.For example, someone driving many miles at high speeds over a givenperiod may present a higher insurance risk compared with someone whodrove relatively few miles, and only at low speeds. Such information mayprovide much more insight as to the driver risk than could be gained bya figure of the number of miles driven per year.

Other additional data may be collected and presented in graphical formataccording to certain example embodiments of the disclosed technology.For example, a breakdown of miles driven per time of day 410 may bepresented to provide additional risk insight. For example, many milesdriven within the 2:00 am hour time slot may indicate an elevated risk.

An example method 500 for monitoring and communicating telematicinformation will now be described with reference to the flowchart ofFIG. 5. The method 500 starts in block 502, and according to an exampleimplementation includes receiving, at an Operational Measurement Unit(OMU), an operation indication associated with a first vehicle, whereinthe OMU comprises an operational measurement component configured toadvance an operational count in response to receiving the operationindication. In block 504, the method 500 includes receiving, at aVehicular Identification Unit (VIU), vehicular identification datarelated to the first vehicle, wherein the vehicular identification datacomprises identification (ID) data representing the first vehicle. Inblock 506, the method 500 includes transmitting the operational countand the ID data wirelessly to a mobile computing device. In block 508,the method 500 includes receiving, at the mobile computing device, thetransmitted operational count and the ID data. In block 510, the method500 may optionally include (as indicated by the dashed box) storing atleast a portion of the operational count and the ID data in a memoryassociated with the mobile computing device. In block 512, the method500 includes receiving, with the mobile computing device, sensor datafrom one or more sensors associated with the mobile computing device. Inblock 514, the method 500 includes transmitting, by the mobile computingdevice to a remote server, telematics data, wherein the telematics datacomprises at least a portion of one or more of the operational count,the ID data, and the sensor data.

In an example implementation the OMU may be in communication with a portassociated with the first vehicle. In one example implementation, theport may be an OBD port. According to an example implementation, theoperation indication may sensed by the OMU when the first vehicle is inan operating state. In an example implementation, transmitting theoperational count and the ID data wirelessly to the mobile computingdevice may be based at least in part on the operation indication. In oneexample implementation, the mobile computing device may be configured toreceive the sensor data based at least in part on the operationindication.

According to an example implementation of the disclosed technology,transmitting operational count and the ID data wirelessly to the mobilecomputing device may include transmitting data over one or moreestablished communications channels in which the OMU and/or VIU arepaired with the mobile computing device. Certain example embodimentsinclude comparing, a first operational count with a second operationalcount, for example where the first and second operation count may bederived or associated from the received operational count data. In oneexample implementation, the first operational count may correspond to apreviously stored end-of-vehicle-operation operational count, and thesecond operational count may correspond to a start-of-vehicle-operationoperational count. Example embodiments may include providing an alert inresponse to the first operational count and second operational countdiffering by greater than a predefined threshold. In one exampleimplementation, providing the alert may include one or more oftransmitting, by the mobile computing device, a notification to theremote server, and generating a message for output by the mobilecomputing device. In another example implementation, providing the alertmay be performed by a server in communication with the mobile computingdevice.

Example embodiments of the disclosed technology may include receivingand storing, at the remote server, the transmitted telematics dataassociated with the first vehicle. Example embodiments of the disclosedtechnology may include receiving and storing, at the remote server,telematics data associated with a plurality of vehicles. Exampleembodiments of the disclosed technology may include comparing at least aportion of the received telematics data from the first vehicle withtelematics data from the plurality of vehicles to determine one or morerisk factors associated with operating the first vehicle. Exampleembodiments of the disclosed technology may include receiving andstoring, at the remote server, the transmitted telematics dataassociated with the first vehicle; and outputting at least a portion ofthe telematics data in graphical format. Example embodiments of thedisclosed technology may include determining, based at least in part onthe received telematics data, one or more entity scenarios comprisingone or more assertions. Example embodiments of the disclosed technologymay include comparing one or more attributes of the received telematicsdata with information from one or more data sources to determine aplurality of correlations. Example embodiments of the disclosedtechnology may include calculating a confidence level associated withthe one or more assertions based at least in part on the determinedplurality of correlations and outputting a score representative of theconfidence level that the received telematics data comprises one or moreattributes that correspond to the one or more assertions.

One embodiment may further include transforming the received telematicsdata, wherein the transforming comprises one or more of formatting,filtering, compressing, or validating the received telematics data.According to certain example embodiments, information from one or moredata sources may include previously stored information having a classtype corresponding to the received telematics data, wherein the classtype comprises accelerometer data, magnetometer data, gyroscope data,clock data, global positioning system (GPS) data, Bluetooth system datacomprising one or more of paring or disconnects, microphone signals, orWi-Fi system data.

In certain embodiments, determining the one or more entity scenarioscomprising one or more assertions includes identifying one or more of anindividual in possession of or associated with the mobile computingdevice, characteristics of an individual in possession of or associatedwith the mobile computing device, and a vehicle in proximity to themobile device and associated with the VIU. Example embodiments of thedisclosed technology may include comparing one or more attributes of thereceived data with information from one or more data sources comprisescomparing one or more of repeat location visits, repeatable events,velocity, acceleration, location at a specific time, body patterns,habits, data attributes indicative of education level, data attributesindicative of age, data attributes indicative of gender, data attributesindicative of behavior risks, or groups of events.

According to an example implementation, a method may further includereceiving and storing, at the remote server, the transmitted telematicdata associated with the first vehicle and receiving and storing, at theremote server, OBD data and the mobile device sensor data associatedwith a plurality of additional vehicles. The method may includecomparing at least a portion of the telematic data to determine riskassociated with certain driving data. The method may further includereceiving and storing, at the remote server, the transmitted telematicdata associated with the first vehicle; and outputting at least aportion of the telematic data in graphical format.

An example implementation of the disclosed technology may include amonitoring system that can include a personal data unit, a communicationunit, and an analysis unit. The personal data unit can receive personaldata about the insurance applicant, including a telephone number orother identifier of a mobile communication device, for example, asmartphone used by an insurance applicant or policyholder. Thecommunication unit may receive location data related to the mobilecommunication device, where the location data describes variouslocations of the mobile communication device over time. In someembodiments of the monitoring system, the communication unit canperiodically contact the mobile communication device itself to receiveperiodic location updates. Alternatively, however, the communicationunit can receive historical location data from a data center, such as amobile service provider, associated with the mobile communicationdevice. The analysis unit can analyze the location data to determinemovements of the mobile communication device and, thus, a pattern ofusage of a motor vehicle used by the insurance applicant. Analysis ofthe location data may be used, for example, by an insurance provider todetermine a level of risk for insuring an applicant.

Certain example embodiments of the disclosed technology may include amobile smartphone application. For example, embodiments of thesmartphone application may be compatible with mobile device operatingsystems (such as Andriod, iOS, Windows, etc.). The smartphoneapplication(s) may be configured to launch and run in the background ofa driver's (or policyholder's) smartphone and may monitor data.According to an example implementation, the monitored data may beuploaded via the policyholder's smartphone data connection to one ormore remote servers, where the information may be stored and analyzed.Beyond an initial configuration/pairing with the one or more peripheraldevices, there may be no need for additional user interaction via thesmartphone application.

In accordance with an example implementation, once the driving data isuploaded to the remote server and stored in a database, entitiesauthorized to access driving information for the particular driver maybe able to receive a file of driving information in a standard outputformat. Once sufficient data has been collected, a driving model may becreated for which a driving score may be determined based on themonitored data. According to an example implementation, authorizedentities may be able to receive or access the driving score for anindividual driver based upon the individualized data stored within thedatabase.

According to certain example embodiments, an authorized entity may beable to access information about their driving data in aconsumer-friendly format. In one instance, the authorized entity may bethe driver of the vehicle and the policyholder. In another instance, theauthorized entity may be the policyholder, but not the driver (forexample, a parent of a driver). In another example embodiment, theauthorized entity may be responsible, or otherwise associated with avehicle fleet, and may access the data to better understand informationrelated to the various vehicles and/or drivers. For example, accordingone embodiment, an authorized entity may access information via awebsite (as discussed with reference to FIG. 4 above). Additional waysof accessing and/or viewing consumer-friendly driving information mayinclude integration of the information into a web site (for example, viadirect web API calls), or through simple reports that can be provided aspart of a normal consumer disclosure process within existing framework.

Certain example embodiments of the disclosed technology may rely on anindependent database. Collected data, for example, may be supplied tothe independent database by a combination of data elements from themobile computing device and the vehicle identification unit device thatis paired to the mobile computing device.

In accordance with an example implementation, the mobile application maybe configured to communicate with various peripheral in-vehicle devices,such as for example, the ELM-based OBD-II device and/or BlueDriverOBD-II device. One example embodiment may rely on a Bluetooth connectionto provide a wireless communication channel to connect the one or moreperipheral devices and interface with the smartphone or mobile computingdevice. However, it will be recognized that any suitable communicationchannel may be used for delivering information from the one or moreperipheral devices to the mobile computing device without departing fromthe scope of the disclosed technology.

In an example implementation, a detected event may indicate thebeginning of “trip” and may cause the start the datacollection/transmission. For example, the event may be when the one ormore peripheral devices 104 are “woken up” when the vehicle 102 isstarted and the connection between the one or more peripheral devices104 is established with the mobile device 106. In an exampleimplementation, another event may be utilized to indicate the end of“trip” and end the data collection/transmission. For example, this eventmay be when the one or more peripheral devices 104 is “put to sleep”when the vehicle 102 is turned off and the connection between the one ormore peripheral devices 104 is terminated with the mobile device 106.One example of this implementation is the use of an OperationalMeasurement Unit (OMU) 107 (such as a Hobbs meter) associated with theone or more peripheral devices 104, and will be further explained indetail below with reference to FIG. 7.

FIG. 6 is a block diagram of an illustrative system usage scenario 600according to an example embodiment of the disclosed technology, whichmay be utilized, at least in part to confirm an identity of anindividual 602 based, for example, on signature data obtained viasensors associated with a mobile computing device 106. In oneembodiment, an individual 602 may be in possession of a mobile computingdevice 106 that may be in communication with a server 608 via a cellularor Wi-Fi network 606. In accordance with an example embodiment, theserver 608 may analyze data received from the mobile computing device106. In one embodiment, the server 608 may filter or select certaindata. According to certain example embodiments, the server 608 may storeat least a portion of the data received from the mobile computing device106 in a memory or data storage repository 610. Accordingly, previouslystored data from the data storage repository 610 may be retrieved andcompared with received data from the mobile computing device 106.

FIG. 7 depicts an example telematics system 700, according to an exampleembodiment of the disclosed technology. According to certain exampleembodiments, a processing system 701 may be utilized to receive,process, filter, score, compare, etc., information obtained from amobile computing device 106. According to an example embodiment, the aprocessing system 701 may include a processing engine 702 that includesa memory 704, one or more processors 706 in communication with thememory 704, one or more input output interfaces 708, and one or morenetwork interfaces 710.

In an example embodiment, the memory 704 may include an operating system712, data 714, and a number of modules for handling data. For example,the memory 704 may include one or more filter modules 716 that may beutilized to modify received data. For example, the one or more filtermodules 716 may perform one or more of the following: bandwidthfiltering, noise reduction, artifact isolation, band-limiting, sampling,digital signal processing, etc. In accordance with certain exampleembodiments, the memory 704 may also include one or more comparisonmodules 718. For example, one or more comparison modules 718 may beutilized to determine similarities or differences between incoming datafrom the mobile computing device 106 and retrieved data that has beenpreviously stored in memory 704 or in a data repository 726. Accordingto certain example embodiments, the one or more comparison modules 718may be utilized to perform correlation, convolution, frequency analysis,matching, transformation, vector analysis, multivariate analysis, etc.

In accordance with example embodiments of the disclosed technology, thememory 704 may include one or more scoring modules 720. In certainembodiments, the scoring modules 720 may be utilized for calculating aconfidence level associated with one or more assertions based at leastin part on the processing by the one or more comparison modules 718. Inaccordance with certain example embodiments, a score representative ofthe confidence level that the received plurality of data includes one ormore attributes that correspond to the one or more assertions may beoutput, for example, to a display 722 via the input/output interface708, or it may be sent to a local or remote computer 724 and/or a datarepository 726.

According to example embodiments of the disclosed technology, and withcontinued reference to FIG. 7, the mobile computing device 106 maycommunicate with the processing system 701 via any available channel729, which may include, but is not limited to, one or more wirelesscellular communications channels, Wi-Fi, Bluetooth, Zigbee, etc. Asdepicted in FIG. 7, a number of sensors or functions associated with themobile computing device 106 may provide information or data that may beprocessed by the processing system 701. For example, according to oneembodiment, SSID information from a nearby Wi-Fi hotspot may be obtainedby the mobile computing device 106 Wi-Fi transceiver 730 to providelocation data.

In an example embodiment, a magnetometer, an accelerometer 732 and/orgyroscope 734 associated with the mobile computing device 106 mayprovide tilt, attitude, or angle information. In accordance with anexample embodiment, a clock 736 may be utilized for time stamping some,any, or all of the data sent from the mobile computing device 106 to theprocessing system. In an example embodiment the clock 736 may beutilized to time certain events. In another example embodiment, theclock 736 may be utilized for mirroring time provided by the OperationalMeasurement Unit (OMU) 107 (as will be described below).

In accordance with certain example embodiment, a global positioningsystem (GPS) 738 may provide location data. In certain exampleembodiments, a Bluetooth transceiver 740 may provide information such apairing and disconnects with other Bluetooth devices. According tocertain example embodiments, a microphone 742 associated with the mobilecomputing device 106 may be utilized for obtaining sounds from a localenvironment in which the mobile computing device 106 resides. Forexample, the microphone 742 may be utilized to pick-up sounds associatedwith automobiles and the processing system 701 may be able to analyzethe sound information to distinguish between vehicles. Other sensors,including RFID tag readers, cameras, etc., may be used in conjunctionwith the mobile computing device 106 to provide additional informationto the processing system 701 in accordance with example embodimentswithout departing from the scope of the disclosed technology.

According to an example embodiment, one or more peripheral device 104may be on communication with the mobile computing device 106. Forexample, the one or more peripheral devices 104 (as previously describedwith reference to FIG. 1) may include one or more of a VIU 103, a VDU105, and/or an OMU 107. In one example implementation, the OMU 107 maybe a device, such as a Hobbs meter, vehicle power activated clock, orthe like. The OMU 107 may be utilized to produce an accumulated countcorresponding to operation of a vehicle. For example, the OMU 107 mayadvance a count when an operation indication 752 is received, signifyingthat the vehicle is running. In an example implementation, example, theOMU 107 may include a memory that saves the last advanced count when(power or) the operation indication 752 is no longer applied. Forexample, the operation indicator 752 may include an indication that theignition of a vehicle is in an “on” state. In another exampleembodiment, the operation indicator 752 may be present when power issupplied to the OMU 107.

In one example embodiment, the OMU 107 may be a stand-alone component.In other example embodiments, the OMU 107 may included as a componentassociated with (or in combination with) the VIU 103 and/or the VDU 105.In an example embodiment of OMU 107, account may start advancing eachinstance that the vehicle is started, continue to advance for theduration of the vehicle operation, then stop advancing when the vehicleis turned off. In an example embodiment, the count may be stored innon-volatile memory so that, upon subsequent operation of the vehicle,the count value starts from the last previously generated count value(and saved to non-volatile memory) just prior to the vehicle beingturned-off in the previous period of operation.

In an example implementation of the disclosed technology, the time countfrom the OMU 107 may be communicated to the mobile computing device 106(for example, wirelessly when paired). In one example implementation,the count may be used to update a “mirrored” time count on the mobilecomputing device to synchronize with the operational count on the OMU107. In one example embodiment, synchronization may be handled, in partby the in conjunction with the clock 736. In another example embodiment,synchronization or the mirrored time count on the mobile computingdevice may rely only on the data received from the OMU 107. In oneexample embodiment, the application on the mobile computing device, uponparing, may compare its last saved mirrored time count to the time countthat is being communicated by the OMU 107.

In one scenario, if the operational count representation on the mobilecomputing device 106 matches (or is within a small predetermined errorrange) of the operational count representation on the OMU 107, then itmay be concluded that the vehicle has been monitored by the mobilecommunication device during its previous operation. In another scenario,if the counts on the OMU 107 do not match those of the stored mirroredcounts on the mobile communication device 106, or if they differ morethan a predetermined threshold, then it may be concluded that thevehicle was driven or otherwise operated without being monitored by themobile communications device. For example, someone other than theprimary policyholder may have driven the vehicle, or the mobilecommunications device may have been powered down or not present. Suchinformation may indicate that the vehicle was operated without beingmonitored by a specific mobile computing device. In one exampleembodiment, any discrepancy between the stored operational countrepresentation on the mobile computing device 106 and the OMU 107 may besaved, reported, etc.

FIG. 8 is a block diagram of an example entity scenario and assertionprocess 800. According to an example embodiment of the disclosedtechnology, certain information 802 may be received from a mobilecomputing device 106. The information 802 may include classes comprisingone or more of location, acceleration, angular position, status, time,sounds, etc. In accordance with an example embodiment, data from one ormore data sources 804 (stored data for example, from a data repository)may be received and compared with the information 802 received from themobile computing device 106. According to an example embodiment,correlations 806 between the classes of information 802 and data 804 maybe determined for a plurality of vectors. For example, a first vectormay correspond to “Bob”; a second vector may correspond to “Jane”; athird vector may correspond to a third entity “X” who may or may not beassociated with Bob or Jane. Bob and Jane may represent a marriedcouple, for example, who may share a vehicle, and may also share amobile computing device 106. Example embodiments of the disclosedtechnology may provide a determination of who is most likely (Bob, Jane,or X) to be carrying the mobile device, and/or which vehicle they areutilizing at a given time.

In an example embodiment, information 802 may be gathered for Bob, Jane,and X, and stored as historical data 804 for such comparisons with newinformation 802. For example, correlations between the new information802 and the historical data 804 may be made for each vector (Bob, Jane,and X). FIG. 8 depicts that the location data, the angle of the device,a walking signature, and an acceleration profile all likely correspondto the historical data 804 associated with the Bob vector. However, carvibration correlation indicates that it corresponds with a third carvector X. According to certain example embodiments, the correlations maybe fused 808 to determine 812 a confidence 812 of a set of assertions810. For example, one possible assertion 810 may be that Jane is drivingJane's car to the store. Another assertion 810 may be that Bob isdriving Jane's care to the gym, and so forth. However, the correlation806 obtained from the comparison of the vector information 802 from themobile computing device 106 and the data 804 obtained from the datasources indicate that the assertion 810 combination with the highestconfidence 814 is that Bob is driving an unknown car (X) to the gym.Example embodiments of the disclosed technology may include more or lessvectors, and confidence levels of certain assertions may be based onmore or less data or information classes than are presented in theexample shown in FIG. 8.

An example method 900 will now be described with reference to theflowchart of FIG. 9. The method 900 starts in block 902, and accordingto an example embodiment of the disclosed technology includes receiving,at a mobile computing device, and from a Vehicle Identification Unit(VIU), identification (ID) data representing a first vehicle. In block904, the method 900 includes receiving, by the mobile computing device,sensor data from one or more sensors associated with the mobilecomputing device. In block 906, the method 900 includes transmitting, bythe mobile computing device, telematics data, wherein the telematicsdata comprises at least a portion of one or more of the ID data and thesensor data.

According to certain example embodiments, the method may further includereceiving, at an Operational Measurement Unit (OMU), an operationindication associated with the first vehicle, wherein the OMU includesan operational measurement component configured to advance anoperational count in response to receiving the operation indication.Certain example embodiments may include transmitting data representingthe operational count wirelessly to the mobile computing device,receiving, at the mobile computing device, the transmitted operationalcount data, and transmitting, by the mobile computing device, thetelematics data, wherein the telematics data further includes theoperational count data.

In certain example embodiments, the operation indication may be sensedby the OMU when the first vehicle is in an operating state. Certainexample embodiments may include wirelessly transmitting datarepresenting the operational count to the mobile computing device basedat least in part on the sensed operation indication. In certain exampleembodiments the mobile computing device may be configured to receive thesensor data based at least in part on the operation indication receivedby the OMU.

According to certain example embodiments, the method may further includewirelessly transmitting, to the mobile computing device from a VehicleData Unit (VDU), vehicular information corresponding to the firstvehicle; receiving, at the mobile computing device, the vehicularinformation; and transmitting, by the mobile computing device,telematics data, wherein the telematics data further comprises thevehicular information. According to an example implementation of thedisclosed technology, the method may further include transmitting the IDdata representing the first vehicle from a Vehicle Data Unit (VDU) tothe VIU.

According to an example implementation of the disclosed technology, anembodiment may include wirelessly transmitting to the mobile computingdevice from a Vehicle Data Unit (VDU), vehicular informationcorresponding to the first vehicle, receiving, at the mobile computingdevice, the vehicular information; and transmitting, by the mobilecomputing device to a remote server, telematics data, wherein thetelematics data may further include the vehicular information.

In an example embodiment, a method may include determining, based atleast in part on the received telematics data, one or more entityscenarios comprising identifying one or more of an individual inpossession of or associated with the mobile computing device,characteristics of an individual in possession of or associated with themobile computing device, and a vehicle in proximity to the mobile deviceand associated with the VIU.

In an example embodiment, the sensor data comprises accelerometer data,magnetometer data, gyroscope data, clock data, global positioning system(GPS) data, Bluetooth system data comprising one or more of paring ordisconnects, microphone signals, and Wi-Fi system data. In an exampleembodiment, the telematics data further comprises one or more of repeatlocation visits, repeatable events, velocity, acceleration, location ata specific time, body patterns, habits, data attributes indicative ofeducation level, data attributes indicative of age, data attributesindicative of gender, data attributes indicative of behavior risks, orgroups of events.

Example embodiments may further include comparing a first time countwith a second time count, wherein the first time count corresponds to apreviously stored power-down time count, and wherein the second timecount corresponds to a power-up time count; and providing an alert whenthe first time count and second time count differ by greater than apredefined threshold, wherein providing the alert comprises one or moreof transmitting by the mobile computing device a notification to theremote server, and generating a message for output by the mobilecomputing device.

Example embodiments may further include receiving and storing, at theserver, the transmitted telematics data associated with the firstvehicle; receiving and storing, at the remote server, telematics dataassociated with a plurality of vehicles; and comparing at least aportion of the received telematics data from the first vehicle withtelematics data from the plurality of vehicles to determine one or morerisk factors associated with operating the first vehicle.

Example embodiments may further include receiving and storing, at theremote server, the transmitted telematics data associated with the firstvehicle; and outputting at least a portion of the telematics data ingraphical format. An example embodiment may include determining, basedat least in part on the received telematics data, one or more entityscenarios comprising one or more assertions; comparing one or moreattributes of the received telematics data with information from one ormore data sources to determine a plurality of correlations; calculatinga confidence level associated with the one or more assertions based atleast in part on the determined plurality of correlations; andoutputting a score representative of the confidence level that thereceived telematics data comprises one or more attributes thatcorrespond to the one or more assertions.

Example embodiments may further include transforming the receivedtelematics data, wherein the transforming comprises one or more offormatting, filtering, compressing, or validating the receivedtelematics data. In an example embodiment the information from one ormore data sources comprises previously stored information having a classtype corresponding to the received telematics data, wherein the classtype comprises accelerometer data, magnetometer data, gyroscope data,clock data, global positioning system (GPS) data, Bluetooth system datacomprising one or more of paring or disconnects, microphone signals, orWi-Fi system data.

In an example embodiment, determining the one or more entity scenarioscomprising one or more assertions comprises identifying one or more ofan individual in possession of or associated with the mobile computingdevice, characteristics of an individual in possession of or associatedwith the mobile computing device, and a vehicle in proximity to themobile device.

In an example embodiment, comparing one or more attributes of thereceived data with information from one or more data sources comprisescomparing one or more of repeat location visits, repeatable events,velocity, acceleration, location at a specific time, body patterns,habits, data attributes indicative of education level, data attributesindicative of age, data attributes indicative of gender, data attributesindicative of behavior risks, or groups of events.

In accordance with an example embodiment, certain requirements may bemet, for example, in order to capture and monitor appropriate telematicdata. For example, in one embodiment, the GPS sensor may be required tobe active in the mobile device 106 for participation. GPS data, forexample, may be used to determine speed, acceleration,deceleration/braking, and distance traveled. According to an exampleimplementation, GPS data may be collected on a second by second basis.According to an example implementation, an accelerometer or magnetometerassociated with the mobile device 106 may be used to collect data, forexample, at a frequency of about every 1/10 second, or approximately 10Hz.

In accordance with certain example embodiments, analytics may begenerated based on a population of drivers, and certain irregularitiesin the data from individual drivers may be detected and characterized,filtered, etc. For example, the analytics may be utilized to detect“tampering” events or situations where the GPS sensor was disabled. Suchinformation may be scored and provided to any number of entities, forexample, to alert them to a possible high-risk driver.

According to certain example embodiments, the mobile applicationinstalled and running on the driver's mobile device 106 may be targetedsuch that battery usage is <5% of the overall expected battery life whenthe device is in stand-by mode, and <20% of the overall expected batterylife when the device is in active mode. In an example implementation,the mobile application may be targeted so monthly data usage is <5 MBwhen connected to cellular plan.

According to example embodiments of the disclosed technology, severalattributes that may be derived from the monitoring the vehicletelematics, according to example embodiments of the disclosedtechnology. For example, the vehicle VIN may be derived from the VIU103, but the number of accelerations above a certain threshold may bederived by the sensors associated with the smartphone 106 via a mobileapplication. According to certain example embodiments of the disclosedtechnology, engine operational time counts may be derived from the OMU107. In certain example embodiments, vehicular data presented at a port110 associated with a vehicle 102 may be received and transmitted to thesmartphone 106 by the VDU 105. In certain example embodiments, otheranalytics and attributes may be further refined or derived at the remoteserver.

Certain details for obtaining the telematic data in a may be carried outin accordance with an example embodiment of the disclosed technology.For example, the mobile application may require the user to manuallypair the mobile device with one or more peripheral devices, for example,as new Bluetooth connection. In one example embodiment, pairing may beinitiated at the original setup and may automatically reconnect with theperipheral device each time the vehicle is started, marking thebeginning of a trip. If the Bluetooth (or other wireless) connection islost, then the application may automatically try to re-establish theconnection with the mobile device. The application may recognize thestart of a trip as when the peripheral device connects with the mobiledevice via the established wireless connection because there may be databeing transmitted by the peripheral device. The application mayrecognize the end of a trip when the connection with the one or moreperipheral devices and the mobile device is terminated by theestablished wireless connection because there may no longer be any databeing transmitted from the one or more peripheral devices. In certainexample embodiments, the application may automatically restart if themobile device is restarted, as long as the application was running priorto the device restart.

According to an example embodiment, the participant (i.e., applicant,insured, drive, etc.) may be required to start the mobile applicationinitially on the mobile device after installation. The mobileapplication may rely on the GPS sensor to collect data on a second bysecond basis to derive speed, acceleration, deceleration and distance.If the GPS sensor is not on when the peripheral device is initiated, themobile application may turn it on and may prompt the participant ifnecessary. If the GPS sensor is disabled or is dropped during a trip,the trip may be ended and the collected data may be transmitted. In oneembodiment, the application may omit any prompt that the GPS sensor hasbeen lost, but may instead, provide a prompt for restart of the sensorat the beginning of the next trip. The mobile application may notcollect or transmit data if the application is stopped by theparticipant.

In an example implementation, a Telematics ID may be sent for theregistered mobile communications device, via the participants chosendelivery method, so that pairing between the mobile device and the oneor more peripheral devices can be established. In one embodiment, themobile application may require the user to login to the mobile device atinitial setup/pairing of the device with the Telematics ID (which may besystematically generated and supplied via text message) after the userhas completed the registration process on a web site, for example.

According to certain example implementation of the disclosed technologythere may not be any required participant interaction if all of thefollowing are true: (1) the mobile application is correctly installed onthe mobile device (if the application is not correctly installed, theparticipant should re-install the application); (2) the mobileapplication is started on the mobile device (if the application is notstarted, the participant should restart the application on the device);(3) the application has been successfully registered with a uniqueTelematics ID (if the application is not correctly registered, theparticipant should re-register the device and/or contact CustomerSupport); (4) the device is paired to the one or more peripheraldevices, such as the VIU 103 (if the device is not correctly paired, theparticipant should reestablish the wireless connection); (5) the mobiledevice is within the cellular provider's signal area for datatransmission (if the device is not in the cellular provider's signalarea, the transmission may need to wait for the participant to reenterthe provider's area).

According to an example embodiment, one or more of the followingparticipant information may be gathered, and may be included in the webpage or report made available to an authorized participant and/or theinsurance carrier: Participant First Name; Participant Last Name;Carrier Name; Policy Number; Date of Birth; Driver's License Number;VIN; Mobile Phone #; Telematics ID; Email Address; Street Address; City;State; and Zip.

In accordance with an example embodiment, the following information maybe included in the web page or report made available to the participantand/or authorized entity. Vehicle Make; Vehicle Model; Vehicle Year;Date and time of last successful data sync; and trip-level statistics.Tables 2-7 below summarize example data that may be collected andarchived and/or included in the web page or report made available to anauthorized participant or authorized entity.

TABLE 2 Trip level statistics Start End Distance Average Max DurationTime Time (miles) Speed Speed (hh:mm) 10:15 a 10:47 a 15 m 33 mph 55 mph00:32  3:31 p  4:35 p 39 m 48 mph 62 mph 01:04

TABLE 3 Monthly summary Total Average Average Total Driving TotalDistance Distance Distance Driving Time Month Trips (miles) per Day perTrip Time per Day January 63 1246 m 40.2 m 19.8 m 84:26 01:55 February52 1186 m 42.5 m 22.8 m 78:31 00:52

TABLE 4 Day of week statistics Total Average Day of Total DistanceDistance Total Driving Driving Time Week Trips (miles) per Trip Time perDay Monday 3  64.8 m 21.3 m 3:21 1:07 Tuesday 7 174.3 m 24.9 m 8:31 1:18

TABLE 5 Time of day statistics Total Average Total Driving TotalDistance Distance Driving Time per Time of Day Trips (miles) per TripTime Bracket 8:00 a-9:00 a 3 64.8 m 21.3 m 3:21 1:07  9:00 a-10:00 a 228.4 m 14.2 m 1:50 00:55  10:00 a-11:00-a 7 174.3 m  24.9 m 8:31 1:18

TABLE 6 Monthly driving events # of Hard Average Max Month # of HardBrakes Accelerations Speed Speed January 14 36 40.2 m 68.3 m February 1931 42.5 m 67.8 m

TABLE 7 Driving periods without monitoring Date and time of Previouslymatched Unmonitored Unmonitored Hobbs meter count and mirrored countduration Miles Driven 1/4/2012 08:20 am 38 hours  40.2 miles 2/8/201305:32 pm 88 hours 165.4 miles

One of skill in the art will recognize that the above examples arepresented only for illustrative purposes. Other information can beincluded, substituted, or combined in various embodiments of the system100, system 300, and/or the system 700.

As discussed above in detail, embodiments of the monitoring systemdisclosed herein may provide an effective means of determining aninsurance risk for a vehicle insurance applicant. By monitoring a mobilecommunication device of the driver, the monitoring system can monitordriving to determine certain driving risks, thereby establishing aninsurance premium that accurately reflects the insurance risk involved.

According to example implementations, certain technical effects can beprovided, such as creating certain systems and methods that provide realdriving data for assessing risks associated with an insurance applicant.Example implementations of the disclosed technology can provide thefurther technical effects of providing systems and methods for obtainingdriving analytics for a plurality of drivers for use in establishingrisks associated with certain driving behaviors.

In example implementations of the disclosed technology, the telematicsmonitoring system 100 may include any number of hardware and/or softwareapplications that are executed to facilitate any of the operations. Inexample implementations, one or more I/O interfaces may facilitatecommunication between the telematics monitoring system 100 and one ormore input/output devices. For example, a universal serial bus port, aserial port, a disk drive, a CD-ROM drive, and/or one or more userinterface devices, such as a display, keyboard, keypad, mouse, controlpanel, touch screen display, microphone, etc., may facilitate userinteraction with the telematics monitoring system 100. The one or moreI/O interfaces may be utilized to receive or collect data and/or userinstructions from a wide variety of input devices. Received data may beprocessed by one or more computer processors as desired in variousimplementations of the disclosed technology and/or stored in one or morememory devices.

One or more network interfaces may facilitate connection of thetelematics monitoring system 100 inputs and outputs to one or moresuitable networks and/or connections; for example, the connections thatfacilitate communication with any number of sensors associated with thesystem. The one or more network interfaces may further facilitateconnection to one or more suitable networks; for example, a local areanetwork, a wide area network, the Internet, a cellular network, a radiofrequency network, a Bluetooth enabled network, a Wi-Fi enabled network,a satellite-based network any wired network, any wireless network, etc.,for communication with external devices and/or systems.

Example embodiments include storing at least a portion of the receivedplurality of data in a centralized data repository. According to anexample embodiment, the storing further includes transforming thereceived data, wherein the transforming may include one or more offormatting, filtering, compressing, or validating the received data.

According to example embodiments, information from one or more datasources includes previously stored information having a class typecorresponding to the received plurality of data, wherein the class typesare: accelerometer data, magnetometer data, gyroscope data, clock data,global positioning system (GPS) data, Bluetooth system data that caninclude one or more of paring or disconnects, microphone signals, orWi-Fi system data.

According to an example embodiment, receiving the plurality of data fromthe mobile device includes receiving data from one or more of a cellularphone, a tablet computer, a handheld mobile computing device, or awearable mobile device. In certain example embodiments, determining oneor more entity scenarios include one or more assertions identifying oneor more of an individual in possession of or associated with the mobiledevice, characteristics of an individual in possession of or associatedwith the mobile device, or one or more vehicles in proximity to themobile device. In certain example embodiments, comparing one or moreattributes of the received data with information from one or more datasources includes comparing one or more of repeat location visits,repeatable events, velocity, acceleration, location at a specific time,body patterns, habits, data attributes indicative of education level,data attributes indicative of age, data attributes indicative of gender,data attributes indicative of behavior risks, or groups of events.According to example embodiments, the comparing includes one or more ofa correlation, a convolution, frequency analysis, a matching, atransformation, vector analysis, or multivariate analysis.

According to example embodiments, certain technical effects can beprovided, such as creating certain systems and methods that enableidentifying one or more of an individual in possession of or associatedwith the mobile device, characteristics of an individual in possessionof or associated with the mobile device, or one or more vehicles inproximity to the mobile device. Example embodiments of the disclosedtechnology can provide the further technical effects of providingsystems and methods for comparing one or more of repeat location visits,repeatable events, velocity, acceleration, location at a specific time,body patterns, habits, data attributes indicative of education level,data attributes indicative of age, data attributes indicative of gender,data attributes indicative of behavior risks, or groups of events todetermine a confidence of an assertion.

In example embodiments of the disclosed technology, the analysis system200 may include any number of hardware and/or software applications thatare executed to facilitate any of the operations. In exampleembodiments, one or more I/O interfaces may facilitate communicationbetween the analysis system 200 and one or more input/output devices.For example, a universal serial bus port, a serial port, a disk drive, aCD-ROM drive, and/or one or more user interface devices, such as adisplay, keyboard, keypad, mouse, control panel, touch screen display,microphone, etc., may facilitate user interaction with the analysissystem 200. The one or more I/O interfaces may be utilized to receive orcollect data and/or user instructions from a wide variety of inputdevices. Received data may be processed by one or more computerprocessors as desired in various embodiments of the disclosed technologyand/or stored in one or more memory devices.

One or more network interfaces may facilitate connection of the analysissystem 200 inputs and outputs to one or more suitable networks and/orconnections; for example, the connections that facilitate communicationwith any number of sensors associated with the system. The one or morenetwork interfaces may further facilitate connection to one or moresuitable networks; for example, a local area network, a wide areanetwork, the Internet, a cellular network, a radio frequency network, aBluetooth enabled network, a Wi-Fi enabled network, a satellite-basednetwork any wired network, any wireless network, etc., for communicationwith external devices and/or systems.

As desired, embodiments of the disclosed technology may include atelematics system 100, 200, 300, 700 with more or less of the componentsillustrated in FIGS. 1-3 and/or FIGS. 6-8.

Certain embodiments of the disclosed technology are described above withreference to block and flow diagrams of systems and methods and/orcomputer program products according to example embodiments of thedisclosed technology. It will be understood that one or more blocks ofthe block diagrams and flow diagrams, and combinations of blocks in theblock diagrams and flow diagrams, respectively, can be implemented bycomputer-executable program instructions. Likewise, some blocks of theblock diagrams and flow diagrams may not necessarily need to beperformed in the order presented, or may not necessarily need to beperformed at all, according to some embodiments of the disclosedtechnology.

These computer-executable program instructions may be loaded onto ageneral-purpose computer, a special-purpose computer, a processor, orother programmable data processing apparatus to produce a particularmachine, such that the instructions that execute on the computer,processor, or other programmable data processing apparatus create meansfor implementing one or more functions specified in the flow diagramblock or blocks. These computer program instructions may also be storedin a computer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including instruction meansthat implement one or more functions specified in the flow diagram blockor blocks. As an example, embodiments of the disclosed technology mayprovide for a computer program product, comprising a computer-usablemedium having a computer-readable program code or program instructionsembodied therein, said computer-readable program code adapted to beexecuted to implement one or more functions specified in the flowdiagram block or blocks. The computer program instructions may also beloaded onto a computer or other programmable data processing apparatusto cause a series of operational elements or steps to be performed onthe computer or other programmable apparatus to produce acomputer-implemented process such that the instructions that execute onthe computer or other programmable apparatus provide elements or stepsfor implementing the functions specified in the flow diagram block orblocks.

Accordingly, blocks of the block diagrams and flow diagrams supportcombinations of means for performing the specified functions,combinations of elements or steps for performing the specified functionsand program instruction means for performing the specified functions. Itwill also be understood that each block of the block diagrams and flowdiagrams, and combinations of blocks in the block diagrams and flowdiagrams, can be implemented by special-purpose, hardware-based computersystems that perform the specified functions, elements or steps, orcombinations of special-purpose hardware and computer instructions.

Certain embodiments of the disclosed technology are described above withreference to mobile devices. Those skilled in the art recognize thatthere are several categories of mobile devices, generally known asportable computing devices that can run on batteries but are not usuallyclassified as laptops. For example, mobile devices can include, but arenot limited to portable computers, tablet PCs, Internet tablets, PDAs,ultra mobile PCs (UMPCs) and smartphones.

While certain embodiments of the disclosed technology have beendescribed in connection with what is presently considered to be the mostpractical and various embodiments, it is to be understood that thedisclosed technology is not to be limited to the disclosed embodiments,but on the contrary, is intended to cover various modifications andequivalent arrangements included within the scope of the appendedclaims. Although specific terms are employed herein, they are used in ageneric and descriptive sense only and not for purposes of limitation.

This written description uses examples to disclose certain embodimentsof the disclosed technology, including the best mode, and also to enableany person skilled in the art to practice certain embodiments of thedisclosed technology, including making and using any devices or systemsand performing any incorporated methods. The patentable scope of certainembodiments of the disclosed technology is defined in the claims, andmay include other examples that occur to those skilled in the art. Suchother examples are intended to be within the scope of the claims if theyhave structural elements that do not differ from the literal language ofthe claims, or if they include equivalent structural elements withinsubstantial differences from the literal language of the claims.

1. A computer-implemented method comprising: receiving, at a processor,an operation indication associated with starting an operation of avehicle; responsive to receiving the operation indication, advancing anoperational count of a counter; storing the operational count;comparing-the stored operational count with a previously stored count,wherein the previously stored count corresponds to a previously storedoperational count, and wherein the stored operational count correspondsto a start-of-vehicle-operation operational count; and generating,responsive to the comparing, a monitor indication representing whetherthe vehicle has been monitored during a previous operation.
 2. Themethod of claim 1, wherein the operation indication comprises electricalpower being supplied to at least one electronic component associatedwith the vehicle responsive to starting the vehicle.
 3. The method ofclaim 1, wherein the processor is configured to provide an alert inresponse to the stored operational count and the previously stored countdiffering by greater than a predefined threshold.
 4. The method of claim1, further comprising receiving vehicular identification data related tothe vehicle, wherein the vehicular identification data comprisesidentification (ID) data representing the vehicle.
 5. The method ofclaim 1, further comprising: receiving and storing, at a server,telematics data associated with the vehicle; comparing at least aportion of the received telematics data with telematics data associatedwith a plurality of other vehicles to determine one or more risk factorsassociated with operating the vehicle.
 6. The method of claim 1, furthercomprising: determining one or more entity scenarios comprising one ormore assertions; comparing one or more attributes of telematics datawith information from one or more data sources to determine a pluralityof correlations; calculating a confidence level associated with the oneor more assertions based at least in part on the determined plurality ofcorrelations; and outputting a score representative of the confidencelevel that the telematics data comprises one or more attributes thatcorrespond to the one or more assertions.
 7. The method of claim 6,wherein the information from one or more data sources comprisespreviously stored information having a class type corresponding to thetelematics data, wherein the class type comprises one or more ofaccelerometer data, magnetometer data, gyroscope data, clock data,global positioning system (GPS) data, Bluetooth system data comprisingone or more of paring or disconnects, microphone signals, or Wi-Fisystem data.
 8. The method of claim 6, wherein determining the one ormore entity scenarios comprising one or more assertions comprisesidentifying one or more of an individual in possession of or associatedwith the mobile computing device, characteristics of an individual inpossession of or associated with the mobile computing device, and avehicle in proximity to the mobile device and associated withidentification (ID) data representing the vehicle.
 9. The method ofclaim 6, wherein the comparing one or more attributes of the telematicsdata with information from one or more data sources comprises comparingone or more of repeat location visits, repeatable events, velocity,acceleration, location at a specific operational, body patterns, habits,data attributes indicative of education level, data attributesindicative of age, data attributes indicative of gender, data attributesindicative of behavior risks, or groups of events.
 10. The method ofclaim 6, further comprising transforming the telematics data, whereinthe transforming comprises one or more of formatting, filtering,compressing, or validating the received telematics data.
 11. A systemcomprising: at least one memory for storing data and computer-executableinstructions; and at least one processor configured to access the atleast one memory and further configured to execute thecomputer-executable instructions to: receive an operation indicationassociated with starting an operation of a vehicle; advance anoperational count of a counter responsive to the operation indication;store, in the memory, the operational count; compare the storedoperational count with a previously stored count, wherein the previouslystored count corresponds to a previously stored operational count, andwherein the stored operational count corresponds to astart-of-vehicle-operation operational count; generate, responsive tothe comparing, a monitor indication representing whether the vehicle hasbeen monitored during a previous operation; and transmit telematicsdata, wherein the telematics data comprises at least a portion of one ormore of the operational count and the monitor indication.
 12. The systemof claim 11, wherein the operation indication comprises electrical powerbeing supplied to at least one electronic component associated with thevehicle responsive to starting the vehicle.
 13. The system of claim 11,wherein the at least one processor is further configured to provide analert in response to the stored operational count and the previouslystored count differing by greater than a predefined threshold
 14. Thesystem of claim 11, further comprising one or more sensors incommunication with the at least one processor, and wherein the at leastone processor is further configured to receive sensor date from the oneor more sensors; and wherein the telematics data further comprises atleast a portion of the sensor data.
 15. The system of claim 14, whereinthe sensor data comprises accelerometer data, magnetometer data,gyroscope data, clock data, global positioning system (GPS) data,Bluetooth system data comprising one or more of paring or disconnects,microphone signals, and Wi-Fi system data.
 16. The system of claim 11,wherein the at least one processor is further configured to receivevehicle identification (ID) data, and wherein the telematics datafurther comprises at least a portion of the ID data.
 17. The system ofclaim 11, wherein the telematics data further comprises one or more ofrepeat location visits, repeatable events, velocity, acceleration,location at a specific operational, body patterns, habits, dataattributes indicative of education level, data attributes indicative ofage, data attributes indicative of gender, data attributes indicative ofbehavior risks, or groups of events.
 18. The system of claim 11, whereinthe at least one processor is further configured to execute thecomputer-executable instructions to: determine one or more entityscenarios comprising one or more assertions; compare one or moreattributes of telematics data with information from one or more datasources to determine a plurality of correlations; calculate a confidencelevel associated with the one or more assertions based at least in parton the determined plurality of correlations; and output a scorerepresentative of the confidence level that the telematics datacomprises one or more attributes that correspond to the one or moreassertions.
 19. The system of claim 18, wherein the one or more entityscenarios comprise one or more assertions including identifying one ormore of an individual in possession of or associated with the mobilecomputing device, characteristics of an individual in possession of orassociated with the mobile computing device, and a vehicle in proximityto the mobile device and associated with identification (ID) datarepresenting the vehicle.
 20. The system of claim 18, wherein the one ormore attributes of the telematics data comprise one or more of repeatlocation visits, repeatable events, velocity, acceleration, location ata specific operational, body patterns, habits, data attributesindicative of education level, data attributes indicative of age, dataattributes indicative of gender, data attributes indicative of behaviorrisks, or groups of events.